In extracorporeal blood processing, blood is taken out of a human subject, processed (e.g. treated) and then reintroduced into the subject by means of an extracorporeal fluid circuit (“EC circuit”) which is part of a blood processing apparatus. Generally, the blood is circulated through the EC circuit by a blood pump. In certain types of extracorporeal blood processing, the EC circuit includes an access device for blood withdrawal (e.g. an arterial needle or catheter) and an access device for blood reintroduction (e.g. a venous needle or catheter), which are inserted into a dedicated blood vessel access (e.g. fistula or graft) on the subject. Such extracorporeal blood treatments include hemodialysis, hemodiafiltration, hemofiltration, plasmapheresis, bloodbanking, blood fraction separation (e.g. cells) of donor blood, apheresis, extracorporeal blood oxygenation, assisted blood circulation, extracorporeal liver support/dialysis, ultrafiltration, etc.
It is vital to minimize the risk for malfunctions in the EC circuit, since these may lead to a potentially life-threatening condition of the subject. Serious conditions may e.g. arise if the EC circuit is disrupted downstream of the blood pump, e.g. by a Venous Needle Dislodgement (VND) event, in which the venous needle comes loose from the blood vessel access. Such a disruption may cause the subject to be drained of blood within minutes. WO97/10013, US2005/0010118, WO2009/156174, WO2010/149726 and US2010/0234786 all propose various techniques for detecting a VND event by identifying an absence of heart or breathing pulses in a pressure signal from a pressure sensor (“venous pressure sensor”) on the downstream side of the blood pump in the EC circuit.
Recently, it has also been shown to be possible to monitor and analyze the behavior of physiological pressure generators such as the heart or respiratory system, based on pressure recordings in the EC circuit. Various applications are found in WO2010/149726, WO2011/080189, WO2011/080190, WO2011/080191, WO2011/080194 which are incorporated herein by reference. For example, these applications include monitoring a subject's heart pulse rate, blood pressure, heart rhythm, cardiac output, blood flow rate through the blood vessel access (“access flow”), arterial stiffness, as well as identifying signs of stenosis formation within the blood vessel access, predicting rapid symptomatic blood pressure decrease and detecting, tracking and predicting various breathing disorders.
Furthermore, WO2011/080188 proposes a technique for identifying and signaling a reverse placement of the devices for blood withdrawal and blood reintroduction in the vascular access by detecting and analyzing physiological pulses in a pressure signal recorded in the EC circuit.
All of these monitoring techniques presume that the physiological pulses can be reliably detected in the pressure signal. To enable monitoring, it may be necessary to filter the pressure signal for removal or suppression of signal interferences. The signal interferences comprise pressure pulses (“pump pulses”) originating from the blood pump, and may also comprise further interfering pressure pulses, e.g. caused by further pumps, valves, balancing chambers, etc in the EC circuit. It may be a challenging task to properly remove e.g. the pump pulses, since the rate of the physiological pulses and the rate of the blood pump, i.e. the blood flow through the EC circuit, may change over time. If the rate of physiological pulses matches the rate of pump pulses, it is not unlikely that the filtering will remove also the physiological pulses, causing the monitoring technique to fail. Filtering is also rendered difficult by the fact that the pump pulses generally are much stronger than the physiological pulses in the pressure signal.
The prior art comprises WO97/10013 which proposes a filtering technique denoted “notch-equivalent filter”, which presumes that the frequency and phase of the blood pump are known. Sinus signals are generated at the known frequency and at multiples of the known frequency. The sinus signals are input to an adaptive filter, which adapts the amplitude and the phase of each sinus signal to the pressure signal to be filtered. The sinus signals are then subtracted from the pressure signal at the respective amplitude and phase.
The prior art also comprises WO2009/156175, which proposes that the pressure signal is filtered in the time-domain, by subtraction of a predicted signal profile of the pressure pulses originating from the blood pump. The predicted signal profile may be obtained by reference measurements or by simulations. In one implementation, the predicted signal profile is retrieved from a library of pre-stored reference profiles, based on the current operating frequency of the blood pump, and subtracted from the pressure signal, based on timing information given by a dedicated pump sensor or by a control signal for the blood pump. In another implementation, the predicted signal profile is retrieved and subtracted by a best match technique, in which the predicted signal profile is scaled and shifted so as to minimize differences to the pressure signal before the subtraction. In yet another implementation, the predicted signal profile and the pressure signal are input to an adaptive filter structure that operates to adapt its filter coefficients so as to produce an error signal in which the pressure pulses from the blood pump are suppressed.
WO2013/000777 proposes another filtering technique that may be implemented to suppress, in a pressure signal, first pulses that are known to occur in repeating pulse cycles in the pressure signal. Such first pulses may e.g. originate from a blood pump in an extracorporeal blood flow circuit. The proposed technique operates to filter the pressure signal by subtracting, for each current data sample in the pressure signal, a reference value which is calculated as a function of other data sample(s) in the same pressure signal. In one embodiment, the other data sample(s) are cycle-synchronized with the current data sample, which means that they have the same relative location in their respective pulse cycle as the current data sample in the current pulse cycle. Thereby, each reference value will represent an estimation of the instant signal contribution from first pulse(s) within the current pulse cycle. By subtracting this instant signal contribution from the respective current data sample, a time-sequence of output samples can be generated for the current pulse cycle so as to be essentially free of first pulses.
There is a continued need to achieve an improved filtering technique, in terms of one or more of the following: ability to handle changes in the rates of physiological pulses and interference pulses (e.g. pump pulses), ability to handle overlap in frequency and/or time between interference pulses and physiological pulses, complexity of the filtering technique, ability to generate the filtered signal in real time, processing efficiency and memory usage during filtering, accuracy of the filtered signal, and robustness of the filtering technique.